Causal Inference in Statistics: Why, What, and How

 An introductory overview on the goals of causal inference, key quantities, and typical methods will be given for situations where an exposure of interest is set at a chosen baseline (“point exposure”) and the target outcome arises at a later time point, focusing on a binary outcome and continuous exposure. Using the potential outcomes framework, principled definitions of causal effects will be presented along with estimation approaches which invoke the no unmeasured confounding assumption.

Date: May 10, 2023, midnight - May 10, 2023, 11:59 p.m.